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['bom_gen', 'bom_jn', 'bom_knp', 'bom_sachet', 'bom_vtgk', 'bom_ytv', 'hop_dln', 'hop_jn', 'hop_vtg', 'hop_ytv', 'lo_kids', 'lo_ytv', 'loc_dln', 'loc_jn', 'loc_kids', 'loc_ytv', 'pocky', 'tui_gen', 'tui_jn', 'tui_sachet', 'tui_vtgk']pip install ultralyticsplus==0.1.0 ultralytics==8.0.2391from ultralyticsplus import YOLO, render_result
2
3# load model
4model = YOLO('chanelcolgate/chamdiemgianhang-test1')
5
6# set model parameters
7model.overrides['conf'] = 0.25 # NMS confidence threshold
8model.overrides['iou'] = 0.45 # NMS IoU threshold
9model.overrides['agnostic_nms'] = False # NMS class-agnostic
10model.overrides['max_det'] = 1000 # maximum number of detections per image
11
12# set image
13image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'
14
15# perform inference
16results = model.predict(image)
17
18# observe results
19print(results[0].boxes)
20render = render_result(model=model, image=image, result=results[0])
21render.show()